Fragment of neurosecretory protein VGF as a biomarker for Alzheimer&#39;s disease

ABSTRACT

The present invention provides a neurosecretory protein VGF peptide useful in qualifying Alzheimer&#39;s disease status in a patient. In particular, this peptide and modified forms thereof may be used to classify a subject sample as Alzheimer&#39;s disease or non-Alzheimer&#39;s disease. The peptide biomarker can be detected by SELDI mass spectrometry.

This application claims the benefit of priority of U.S. provisionalapplication 60/691,637, filed Jun. 16, 2005. Further, this applicationis a continuation-in-part of PCT Application No. US06/13727 filed Apr.11, 2006, which application claims the benefit of priority of U.S.provisional application 60/673,277, filed Apr. 19, 2005. In addition,this application is a continuation-in-part of U.S. patent applicationSer. No. 10/982,545, filed Nov. 6, 2004, which application claims thebenefit of priority of U.S. provisional application 60/572,617, filedMay 18, 2004 and U.S. provisional application 60/586,503, filed Jul. 8,2004.

FIELD OF THE INVENTION

The invention relates generally to clinical diagnostics.

BACKGROUND OF THE INVENTION

Alzheimer's Disease is a progressive neurodegenerative disorder thatleads to the death of brain cells that cannot be replaced once lost. Theneuropathology is characterized by the presence of amyloid plaques,neurofibrillary tangles, synaptic loss and selective neuronal celldeath. The plaques are a result of abnormal levels of extracellularamyloid beta peptide (AP) while the tangles are associated with thepresence of intracellular hyperphosphorylated tau protein. Symptomsfirst manifest clinically with a decline in memory followed bydeterioration in cognitive function and normal behavior. Age is thesingle most prominent risk factor with the incidence doubling every fiveyears from at the age of 65. Prevalence studies estimated that in 2000the number of persons with AD in the US alone was 4.5 million withnumbers expected to increase almost 3 fold in the next 50 years due tothe rapid growth of the oldest age groups. The increasing number ofdementia patients in the developed world will place an enormous burdenon society and the health care systems.

Despite significant advances in the understanding of AD pathogenesisthere are no drugs that exhibit profound disease-modifying effects.Although great efforts are being made to develop future classes of drugsto slow disease progression, current therapy, typified by theacetylcholinesterase inhibitors, is mainly limited to alleviatingsymptoms (Davis R E et al. (1995) Arzneimittelforschung, 45:425-431).Early diagnosis is a prerequisite for early treatment and will be ofeven greater significance if drugs aimed at slowing neurodegenerationshow a clinical effect.

Current criteria for the clinical diagnosis of AD are largely dependenton the exclusion of other dementias and include neuropsychologicaltesting and neuroimaging, where possible (McKhann G. et al., (1984)Neurology 34:939-944). Although reasonably high accuracy rates of 80-90%using clinical criteria have been reported (Kosunen O et al., (1996)Acta Neuropathol 91:185-193) these studies have been conducted byspecialized centers typically diagnosing patients in the later stages ofdisease. Diagnostic accuracy within routine clinical practice isprobably much lower, particularly during mild or pre-symptomatic stagesof the disease. An unambiguous diagnosis of the disease is currentlyonly possible by examination of brain tissue pathology and is not aclinically feasible process.

Several candidate biomarkers have been discovered in cerebrospinal fluid(CSF) such as Aβ1-42 and tau, which are the major components of amyloidplaques and neurofibrillary tangles, respectively. These tests have beencommercialized and are used routinely in parts of Europe for researchand diagnostic purposes. The diagnostic performance of these biomarkersis not optimal, however, especially with respect to specificity againstother dementias (Blennow K & Hampel H, (2003) Lancet Neurol. 2:605-613).Many other markers have been proposed in both serum and CSF and includeamyloid precursor protein, apoE, isoprostanes (markers of lipidoxidation) and homocysteine. Whether these can be used as diagnosticmarkers has yet to be confirmed (Frank R A. et al. (2003) Neurobiol ofAging 24:521-536).

Therefore, there is an unmet need for simple biochemical tests that candetect AD at an early stage, monitor progression of the disease, anddiscriminate between AD, normal subjects, non-AD dementias and otherneurological disorders.

BRIEF SUMMARY OF THE INVENTION

The present invention fills these needs by providing novel biomarkersand combinations of biomarkers useful for diagnosing Alzheimer'sdisease, as well as methods and kits for using the biomarkers todiagnose Alzheimer's disease.

More specifically, in one embodiment, the invention provides a methodfor qualifying Alzheimer's disease status in a subject comprisingmeasuring at least one biomarker in a biological sample from thesubject, wherein the at least one biomarker is VGF peptide-1, shown inTable 1 (i.e., M6608); and correlating the measurement with Alzheimer'sdisease status. In another related embodiment, the at least onebiomarker is a modified form of the VGF peptide-1, e.g., apost-translationally modified form such as a further truncated orglycosylated form.

The invention provides several different methods of measuring biomarkersuseful for qualifying Alzheimer's disease status. For example, in oneembodiment of the invention, at least one biomarker is measured bycapturing the biomarker on an adsorbent surface of a SELDI probe anddetecting the captured biomarkers by laser desorption-ionization massspectrometry. In one embodiment, the adsorbent comprises an ion-exchangeadsorbent. In a related embodiment, the ion-exchange adsorbent is a Q10Biochip (Ciphergen Biosystems, Inc.). In another embodiment, theadsorbent comprises a biospecific adsorbent.

In some embodiments of the invention, the biomarkers of the invention,e.g., the VGF peptide of Table 1, may be measured by a method other thanmass spectrometry, e.g., by methods that do not involve or,alternatively, do not require a measurement of the mass of the biomarkerto detect or quantify the biomarker's presence in a sample. For example,the biomarkers of the invention may be detected by an immunoassay. Inone embodiment, the invention provides an immunoassay comprising anantibody specific for VGF peptide-1. For example, the N-terminus of theVGF peptide-1 may be specifically detected. In one embodiment, theinvention provides an immunoassay which utilizes an antibody specificfor VGF peptide-1. In a related embodiment, the antibodies recognizedglycosylated or otherwise post-translationally modified forms of VGFpeptide-1.

In a preferred embodiment, the invention provides methods of detectingVGF peptide-1 in bodily fluids, including cerebral spinal fluid (“CSF”).

In a related embodiment, the correlating of biomarker expression withAlzheimer's disease status is performed by a software classificationalgorithm.

In yet another embodiment, the Alzheimer's disease status is selectedfrom Alzheimer's disease and non-Alzheimer's disease. The inventionfurther provides methods of managing subject treatment based on thestatus. In one embodiment, the invention further comprises reporting thesubject's Alzheimer's disease status to the subject. In a relatedembodiment, the invention further comprises recording the Alzheimer'sdisease status on a tangible medium.

For example, if the measurement correlates with Alzheimer's disease,then managing subject treatment comprises monitoring the subject forsymptoms of disease progression and/or regression and/or providingtherapeutic care for the subject. In yet another embodiment, thediagnostic methods of the invention further comprise measuring at VGFpeptide-1 after subject management and correlating the measurement withdisease progression.

In a related embodiment, the invention provides a method for determiningthe course of Alzheimer's disease comprising the step of measuring, at afirst time, at least one biomarker in a biological sample from asubject, wherein the at least one biomarker is VGF peptide-1; measuringone or more of the selected biomarkers in a biological sample from thesubject at a second time; and comparing the first measurement to thesecond measurement to determine the course of the Alzheimer's disease.In a related embodiment, the second measurement in the method occursafter subject management. In a further related embodiment, the methodfor determining the course of Alzheimer's disease status in a subjectcomprises reporting the course of disease status and/or recording thecourse of disease status on a tangible medium.

In another emobdiment, subject management comprises administering acholinesterase inhibitor to the subject.

In another embodiment, the invention provides a method comprisingmeasuring at least one biomarker in a sample from a subject, wherein theat least one biomarker is VGF peptide-1.

In one embodiment, the invention additionally provides a purified VGFpeptide-1. In another embodiment, the invention provides a compositioncomprising a biospecific capture reagent bound to, or capable of bindingto, VGF peptide-1. In a related embodiment, the biospecific capturereagent is an antibody.

In yet another embodiment, the invention provides kits comprising anarticle of manufacture whch in turn comprises a solid support and atleast one capture reagent attached thereto, wherein the capture reagentbinds VGF peptide-1. In another related embodiment, the capture reagentis one which binds VGF peptide-1 with high specificity and selectivity,such as a monoclonal antibody specific for VFG peptide-1. The kits alsocomprise instructions for using the solid support to measure selectedbiomarker(s) and to correlate the measurement(s) with Alzheimer'sdisease status. In one embodiments, the kit further comprisesinstructions for using the solid support to measure VGF peptide-1. Inyet another embodiment, the solid support comprising the capture reagentis a SELDI probe. In still another embodiment, the capture reagent orreagents comprise a hydrophobic adsorbent. In yet another embodiment,the kit comprises a container comprising VGF peptide-1. In anotherrelated embodiment, the capture reagent(s) of the kit comprises an anionexchange chromatography adsorbent.

In yet another embodiment, the invention provides a kit comprising anarticle of manufacture, where the article of manufacture comprises asolid support and at least one capture reagent attached thereto, andwherein the capture agent includes the VGF peptide-1 biomarker, andwhere the kit further comprises a container comprising VGF peptide-1. Inyet another embodiment, the solid support comprising at least oneattached capture reagent is a SELDI probe.

In yet another embodiment, the invention provides a software productcomprising a code that accesses data attributed to a sample, wherein thedata comprises the measurement of at least one biomarker in the sample,where the at least one biomarker includes VGF peptide; and wherein thesoftware further comprises a code that executes a classificationalgorithm that classifies the Alzheimer's disease status of the sampleas a function of the measurement. In a related embodiment, theclassification algorithm classifies the Alzheimer's disease status ofthe sample as a function of the measurement of one or more biomarkers,wherein said one or more biomarkers includes VGF peptide-1.

The invention additionally provides a method comprising the step ofdetecting VGF peptide-1 by mass spectrometry or immunoassay.

In yet another embodiment, the invention provides a method comprisingthe step of communicating to a subject a diagnosis relating toAlzheimer's disease status determined from the correlation of biomarkersin a sample from the subject, wherein said biomarkers include VGFpeptide-1. In a related embodiment, the diagnosis is communicated to thesubject via a computer-generated medium.

In yet another embodiment, the invention provides a method foridentifying a compound that interacts with the VGF peptide-1 biomarker,wherein said method comprises contacting said biomarker with a testcompound, and determining whether the test compound interacts with saidbiomarker.

In another embodiment, the invention provides a method for modulatingthe concentration of a biomarker in a cell, wherein said biomarker isthe VGF peptide-1, and wherein said method comprises the step ofcontacting said cell with an antisense or interfering RNA molecule,wherein said antisense or interfering RNA molecule inhibits expressionof VGF peptide-1 in the cell.

In another embodiment, the invention provides a method of treating acondition in a subject associated with the over-expression of abiomarker in a cell, wherein said biomarker is VGF peptide-1, andwherein said method comprises administering to the subject atherapeutically effective amount of an antisense or interfering RNAmolecule, wherein said antisense or RNA interfering molecule inhibitsexpression of said biomarker in the cell. In a related embodiment, thetreated condition is Alzheimer's disease.

In another embodiment, the invention provides a method for modulatingthe concentration of the VGF peptide-1 in a cell or tissue, comprisingthe steps of contacting the cell or tissue with a protease inhibitor,wherein said protease inhibitor prevents cleavage of native VGF proteinat the positions which lead to the production of VFG peptide-1.

In another embodiment, the invention provides a method of treating acondition in a subject, wherein said method comprises administering to asubject a therapeutically effective amount of a protease inhibitor whichprevents cleavage of native VGF protein. In a related embodiment, thecondition is Alzheimer's disease.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a representative mass spectra for the VGF peptidebiomarker.

DETAILED DESCRIPTION OF THE INVENTION I. Introduction

A biomarker is an organic biomolecule which is differentially present ina sample taken from a subject of one phenotypic status (e.g., having adisease) as compared with another phenotypic status (e.g., not havingthe disease). A biomarker is differentially present between differentphenotypic statuses if the mean or median expression level of thebiomarker in the different groups is calculated to be statisticallysignificant. Common tests for statistical significance include, amongothers, t-test, ANOVA, Kruskal-Wallis, Wilcoxon, Mann-Whitney and oddsratio. Biomarkers, alone or in combination, provide measures of relativerisk that a subject belongs to one phenotypic status or another.Therefore, they are useful as markers for disease (diagnostics),therapeutic effectiveness of a drug (theranostics) and drug toxicity.

II. Biomarkers for Alzheimer's Disease

This invention provides polypeptide-based biomarkers that aredifferentially present in subjects having Alzheimer's disease, inparticular, Alzheimer's disease versus normal (non-Alzheimer's disease).The biomarkers are characterized by mass-to-charge ratio as determinedby mass spectrometry, by the shape of their spectral peak intime-of-flight mass spectrometry and by their binding characteristics toadsorbent surfaces. These characteristics provide one method todetermine whether a particular detected biomolecule is a biomarker ofthis invention. These characteristics represent inherent characteristicsof the biomolecules and not process limitations in the manner in whichthe biomolecules are discriminated. In one aspect, this inventionprovides these biomarkers in isolated form.

The biomarkers were discovered using SELDI technology employingProteinChip arrays from Ciphergen Biosystems, Inc. (Fremont, Calif.)(“Ciphergen”). CSF samples were collected from subjects diagnosed withAlzheimer's disease and subjects diagnosed as normal. The samples wereapplied to SELDI biochips and spectra of polypeptides in the sampleswere generated by time-of-flight mass spectrometry on a Ciphergen PBSIImass spectrometer. The spectra thus obtained were analyzed by CiphergenExpress™ Data Manager Software with Biomarker Wizard and BiomarkerPattern Software from Ciphergen Biosystems, Inc. The mass spectra foreach group were subjected to scatter plot analysis. A Mann-Whitney testanalysis was employed to compare Alzheimer's disease and control groupsfor each protein cluster in the scatter plot, and proteins were selectedthat differed significantly (p<0.0001) between the two groups. Thismethod is described in more detail in the Example Section.

An Alzheimer's disease biomarker thus discovered and identified ispresented in Table 1. The biomarker, VGF peptide-1, is elevated inAlzheimer's disease compared with normal. The VGF peptide biomarker ofTable 1 is a fragment of the neurosecretory protein VGF. Full length VGFis a 616 amino acid protein (SwissProt Accession No. 015240). VGFPeptide-1 has the following amino acid sequence: SQEETPGHRR KEAEGTEEGGEEEDDEEMDP QTIDSLIELS TKLHLPADDV VSIIEEVEE (SEQ ID NO. 1). Thiscorresponds to amino acids 421-479 of the full length protein. Therelationship of VGF peptide-1 to the full-length VGF protein isdescribed in more detail in the Example section. TABLE 1 Up or downregulated in Marker ID, ROC Alzheimer's ProteinChip ® m/z P-Value AUCdisease assay VGF Peptide-1 <0.0001 0.7160 Up- Q10 SPA M6620.0 regulated(anion exchange (predicted surface, pH 9) (Also mass: previouslydetected 6621.98) under same conditions at 6608 D, which is within themargin of error for mass measurement with this instrument.)

The biomarkers of this invention are characterized by theirmass-to-charge ratio as determined by mass spectrometry. Themass-to-charge ratio of each biomarker is provided in Table 1 after the“M.” Thus, for example, M6620.0 has a measured mass-to-charge ratio of6620.0. The peak corresponding to the VGF peptide was previouslyobserved as an approximately 6608 m/z Alzheimer's disease biomarker inU.S. Provisional Patent App. No. 60/673,277, entitled, “Saposin D andFAM 3C are Biomarkers for Alzheimer's Disease; and in PCT/US2004/037994,filed 6 Nov. 2004, entitled, “Biomarkers for Alzheimer's Disease”(International Patent Publication WO 2005/047484). The mass-to-chargeratios were determined from mass spectra generated on a CiphergenBiosystems, Inc. PBS II mass spectrometer. This instrument has a massaccuracy of about +/−0.15 percent. Additionally, the instrument has amass resolution of about 400 to 1000 m/dm, where m is mass and dm is themass spectral peak width at 0.5 peak height. The mass-to-charge ratio ofthe biomarkers was determined using Biomarker Wizard™ software(Ciphergen Biosystems, Inc.). Biomarker Wizard assigns a mass-to-chargeratio to a biomarker by clustering the mass-to-charge ratios of the samepeaks from all the spectra analyzed, as determined by the PBSII, takingthe maximum and minimum mass-to-charge-ratio in the cluster, anddividing by two. Accordingly, the masses provided reflect thesespecifications. Further accuracy in the determination of masses may beobtained by calibrating the instrument using peaks whose identity hasbeen determined (i.e., peaks corresponding to peptides of known aminoacid sequence).

The biomarkers of this invention are further characterized by the shapeof their spectral peak in time-of-flight mass spectrometry. Mass spectrashowing the shape of peak(s) representing the VGF peptide biomarker arepresented in FIG. 1.

The biomarkers of this invention are further characterized by theirbinding properties on chromatographic surfaces. The “ProteinChip assay”column in Table 1 refers to the type of biochip to which the biomarkerbinds. Specifically, VGF peptide binds to anion exchange adsorbents(e.g., the Ciphergen® Q10 ProteinChip® array) at pH 9.0. “SPA” refers tosinapinic acid, an agent used as an energy absorbing matrix inconjunction with the ProteinChip arrays.

The method by which the identity of the VGF peptide was determined isdescribed in the Example Section. For biomarkers whose identify has beendetermined, the presence of the biomarker can be determined by othermethods known in the art.

The preferred biological source for detection of the biomarkers iscerebrospinal fluid (“CSF”). However, the biomarkers may be present inother bodily fluids, e.g., serum, blood, or urine.

The biomarkers of this invention are biomolecules. Accordingly, thisinvention provides these biomolecules in isolated form. The biomarkerscan be isolated from biological fluids, such as CSF. They can beisolated by any method known in the art, based on both their mass andtheir binding characteristics. For example, a sample comprising thebiomolecules can be subject to chromatographic fractionation, asdescribed herein, and subject to further separation by, e.g., acrylamidegel electrophoresis. Knowledge of the identity of the biomarker alsoallows their isolation by immunoaffinity chromatography.

A group of researchers (Yalkinoglu et al.) has independently disclosedan internal fragment of VGF as a biomarker in CSF for Alzheimer'sdisease (International Publication Number WO 2004/019043, published Mar.4, 2004). The publication indicates that the biomarker was found usingSELDI technology. However, the publication indicates that VGF fragmenthas a mass of 4.823 kD and corresponds about to amino acids 378-398 offull-length VGF. Therefore, it is a different fragment than VGFpeptide-1 of this invention, which has a measured mass of about 6620 Daand corresponds to amino acids 421-479 of VGF.

III. Biomarkers and Different Forms of a Protein

Proteins frequently exist in a sample in a plurality of different forms.These forms can result from either or both of pre- andpost-translational modification. Pre-translational modified formsinclude allelic variants, splice variants and RNA editing forms.Post-translationally modified forms include forms resulting fromproteolytic cleavage (e.g., cleavage of a signal sequence or fragmentsof a parent protein), glycosylation, phosphorylation, lipidation,oxidation, methylation, cysteinylation, sulphonation and acetylation.When detecting or measuring a protein in a sample, the ability todifferentiate between different forms of a protein depends upon thenature of the difference and the method used to detect or measure. Forexample, an immunoassay using a monoclonal antibody will detect allforms of a protein containing the eptiope and will not distinguishbetween them. However, a sandwich immunoassay that uses two antibodiesdirected against different epitopes on a protein will detect all formsof the protein that contain both epitopes and will not detect thoseforms that contain only one of the epitopes. In diagnostic assays, theinability to distinguish different forms of a protein has little impactwhen the forms detected by the particular method used are equally goodbiomarkers as any particular form. However, when a particular form (or asubset of particular forms) of a protein is a better biomarker than thecollection of different forms detected together by a particular method,the power of the assay may suffer. In this case, it is useful to employan assay method that distinguishes between forms of a protein and thatspecifically detects and measures a desired form or forms of theprotein. Distinguishing different forms of an analyte or specificallydetecting a particular form of an analyte is referred to as “resolving”the analyte.

Mass spectrometry is a particularly powerful methodology to resolvedifferent forms of a protein because the different forms typically havedifferent masses that can be resolved by mass spectrometry. Accordingly,if one form of a protein is a superior biomarker for a disease thananother form of the biomarker, mass spectrometry may be able tospecifically detect and measure the useful form where traditionalimmunoassay fails to distinguish the forms and fails to specificallydetect to useful biomarker.

One useful methodology combines mass spectrometry with immunoassay.First, a biosepcific capture reagent (e.g., an antibody, aptamer orAffibody that recognizes the biomarker and other forms of it) is used tocapture the biomarker of interest. Preferably, the biospecific capturereagent is bound to a solid phase, such as a bead, a plate, a membraneor an array. After unbound materials are washed away, the capturedanalytes are detected and/or measured by mass spectrometry. (This methodalso will also result in the capture of protein interactors that arebound to the proteins or that are otherwise recognized by antibodies andthat, themselves, can be biomarkers.) Various forms of mass spectrometryare useful for dectecting the protein forms, including laser desorptionapproaches, such as traditional MALDI or SELDI, and electrosprayionization.

Thus, when reference is made herein to detecting a particular protein orto measuring the amount of a particular protein, it means detecting andmeasuring the protein with or without resolving various forms ofprotein. For example, the step of “measuring VGF peptide-1” includesmeasuring a polypeptide whose amino acid sequence corresponds to SEQ IDNO: 1, by means that do not differentiate between various forms of theprotein in a sample (e.g., certain immunoassays) as well as by meansthat differentiate some forms from other forms or that measure aspecific form of the protein (e.g., mass spectrometry). In contrast,when it is desired to measure a particular form or forms of a protein(e.g., any and/or all of M6620 and forms of M6620 modified byphosphorylation, glycosylation, etc.) the particular form or forms arespecified. For example, “measuring M6620” means measuring a polypeptidehaving apparent molecular weight of 6620 Da that, therefore,distinguishes M6620 from other forms of VGF peptide-1.

IV. Detection of Biomarkers for Alzheimer's Disease

The biomarkers of this invention can be detected by any suitable method.Detection paradigms that can be employed to this end include opticalmethods, electrochemical methods (voltametry and amperometrytechniques), atomic force microscopy, and radio frequency methods, e.g.,multipolar resonance spectroscopy. Illustrative of optical methods, inaddition to microscopy, both confocal and non-confocal, are detection offluorescence, luminescence, chemiluminescence, absorbance, reflectance,transmittance, and birefringence or refractive index (e.g., surfaceplasmon resonance, ellipsometry, a resonant mirror method, a gratingcoupler waveguide method or interferometry).

In one embodiment, a sample is analyzed by means of a biochip. Biochipsgenerally comprise solid substrates and have a generally planar surface,to which a capture reagent (also called an adsorbent or affinityreagent) is attached. Frequently, the surface of a biochip comprises aplurality of addressable locations, each of which has the capturereagent bound there.

Protein biochips are biochips adapted for the capture of polypeptides.Many protein biochips are described in the art. These include, forexample, protein biochips produced by Ciphergen Biosystems, Inc.(Fremont, Calif.), Zyomyx (Hayward, Calif.), Invitrogen (Carlsbad,Calif.), Biacore (Uppsala, Sweden) and Procognia (Berkshire, UK).Examples of such protein biochips are described in the following patentsor published patent applications: U.S. Pat. No. 6,225,047 (Hutchens &Yip); U.S. Pat. No. 6,537,749 (Kuimelis and Wagner); U.S. Pat. No.6,329,209 (Wagner et al.); PCT International Publication No. WO 00/56934(Englert et al.); PCT International Publication No. WO 03/048768(Boutell et al.); U.S. Pat. No. 6,902,897 (Tweedie et al.) and U.S. Pat.No. 5,242,828 (Bergstrom et al.).

Detection by Mass Spectrometry

In a preferred embodiment, the biomarkers of this invention are detectedby mass spectrometry, a method that employs a mass spectrometer todetect gas phase ions. Examples of mass spectrometers aretime-of-flight, magnetic sector, quadrupole filter, ion trap, ioncyclotron resonance, electrostatic sector analyzer and hybrids of these.

In a further preferred method, the mass spectrometer is a laserdesorption/ionization mass spectrometer. In laser desorption/ionizationmass spectrometry, the analytes are placed on the surface of a massspectrometry probe, a device adapted to engage a probe interface of themass spectrometer and to present an analyte to ionizing energy forionization and introduction into a mass spectrometer. A laser desorptionmass spectrometer employs laser energy, typically from an ultravioletlaser, but also from an infrared laser, to desorb analytes from asurface, to volatilize and ionize them and make them available to theion optics of the mass spectrometer. The analyis of proteins by LDI cantake the form of MALDI or of SELDI. The analyis of proteins by LDI cantake the form of MALDI or of SELDI.

Laser desorption/ionization in a single TOF instrument typically isperformed in linear extraction mode. Tandem mass spectrometers canemploy orthogonal extraction modes.

SELDI

A preferred mass spectrometric technique for use in the invention is“Surface Enhanced Laser Desorption and Ionization” or “SELDI,” asdescribed, for example, in U.S. Pat. No. 5,719,060 and No. 6,225,047,both to Hutchens and Yip. This refers to a method ofdesorption/ionization gas phase ion spectrometry (e.g., massspectrometry) in which an analyte (here, one or more of the biomarkers)is captured on the surface of a SELDI mass spectrometry probe.

SELDI also has been called “affinity capture mass spectrometry” or“Surface-Enhanced Affinity Capture” (“SEAC”). This version involves theuse of probes that have a material on the probe surface that capturesanalytes through a non-covalent affinity interaction (adsorption)between the material and the analyte. The material is variously calledan “adsorbent,” a “capture reagent,” an “affinity reagent” or a “bindingmoiety.” Such probes can be referred to as “affinity capture probes” andas having an “adsorbent surface.” The capture reagent can be anymaterial capable of binding an analyte. The capture reagent is attachedto the probe surface by physisorption or chemisorption. In certainembodiments the probes have the capture reagent already attached to thesurface. In other embodiments, the probes are pre-activated and includea reactive moiety that is capable of binding the capture reagent, e.g.,through a reaction forming a covalent or coordinate covalent bond.Epoxide and acyl-imidizole are useful reactive moieties to covalentlybind polypeptide capture reagents such as antibodies or cellularreceptors. Nitrilotriacetic acid and iminodiacetic acid are usefulreactive moieties that function as chelating agents to bind metal ionsthat interact non-covalently with histidine containing peptides.Adsorbents are generally classified as chromatographic adsorbents andbiospecific adsorbents.

“Chromatographic adsorbent” refers to an adsorbent material typicallyused in chromatography. Chromatographic adsorbents include, for example,ion exchange materials, metal chelators (e.g., nitrilotriacetic acid oriminodiacetic acid), immobilized metal chelates, hydrophobic interactionadsorbents, hydrophilic interaction adsorbents, dyes, simplebiomolecules (e.g., nucleotides, amino acids, simple sugars and fattyacids) and mixed mode adsorbents (e.g., hydrophobicattraction/electrostatic repulsion adsorbents).

“Biospecific adsorbent” refers to an adsorbent comprising a biomolecule,e.g., a nucleic acid molecule (e.g., an aptamer), a polypeptide, apolysaccharide, a lipid, a steroid or a conjugate of these (e.g., aglycoprotein, a lipoprotein, a glycolipid, a nucleic acid (e.g.,DNA)-protein conjugate). In certain instances, the biospecific adsorbentcan be a macromolecular structure such as a multiprotein complex, abiological membrane or a virus. Examples of biospecific adsorbents areantibodies, receptor proteins and nucleic acids. Biospecific adsorbentstypically have higher specificity for a target analyte thanchromatographic adsorbents. Further examples of adsorbents for use inSELDI can be found in U.S. Pat. No. 6,225,047. A “bioselectiveadsorbent” refers to an adsorbent that binds to an analyte with anaffinity of at least 10⁻⁸ M.

Protein biochips produced by Ciphergen Biosystems, Inc. comprisesurfaces having chromatographic or biospecific adsorbents attachedthereto at addressable locations. Ciphergen's ProteinChip® arraysinclude NP20 (hydrophilic); H4 and H50 (hydrophobic); SAX-2, Q-10 andLSAX-30 (anion exchange); WCX-2, and CM-10 and LWCX-30 (cationexchange); IMAC-3, IMAC-30 and IMAC-50 (metal chelate); and PS-10, PS-20(reactive surface with acyl-imidizole, epoxide) and PG-20 (protein Gcoupled through acyl-imidizole). Hydrophobic ProteinChip arrays haveisopropyl or nonylphenoxy-poly(ethylene glycol)methacrylatefunctionalities. Anion exchange ProteinChip arrays have quaternaryammonium functionalities. Cation exchange ProteinChip arrays havecarboxylate functionalities. Immobilized metal chelate ProteinChiparrays have nitrilotriacetic acid functionalities (IMAC 3 and IMAC 30)or O-methacryloyl-N,N-bis-carboxymethyl tyrosine funtionalities (IMAC50) that adsorb transition metal ions, such as copper, nickel, zinc, andgallium, by chelation. Preactivated ProteinChip arrays haveacyl-imidizole or epoxide functional groups that can react with groupson proteins for covalent binding.

Such biochips are further described in: U.S. Pat. No. 6,579,719(Hutchens and Yip, “Retentate Chromatography,” Jun. 17, 2003); U.S. Pat.No. 6,897,072 (Rich et al., “Probes for a Gas Phase Ion Spectrometer,”May 24, 2005); U.S. Pat. No. 6,555,813 (Beecher et al., “Sample Holderwith Hydrophobic Coating for Gas Phase Mass Spectrometer,” Apr. 29,2003); U.S. Patent Publication No. U.S. 2003-0032043 A1 (Pohl andPapanu, “Latex Based Adsorbent Chip,” Jul. 16, 2002); and PCTInternational Publication No. WO 03/040700 (Um et al., “HydrophobicSurface Chip,” May 15, 2003); U.S. Patent Publication No. US2003-0218130 A1 (Boschetti et al., “Biochips With Surfaces Coated WithPolysaccharide-Based Hydrogels,” Apr. 14, 2003) and U.S. Pat. No.7,045,366 (Huang et al., “Photocrosslinked Hydrogel Blend SurfaceCoatings,” May 16, 2006).

In general, a probe with an adsorbent surface is contacted with thesample for a period of time sufficient to allow the biomarker orbiomarkers that may be present in the sample to bind to the adsorbent.After an incubation period, the substrate is washed to remove unboundmaterial. Any suitable washing solutions can be used; preferably,aqueous solutions are employed. The extent to which molecules remainbound can be manipulated by adjusting the stringency of the wash. Theelution characteristics of a wash solution can depend, for example, onpH, ionic strength, hydrophobicity, degree of chaotropism, detergentstrength, and temperature. Unless the probe has both SEAC and SENDproperties (as described herein), an energy absorbing molecule then isapplied to the substrate with the bound biomarkers.

In yet another method, one can capture the biomarkers with a solid-phasebound immuno-adsorbent that has antibodies that bind the biomarkers.After washing the adsorbent to remove unbound material, the biomarkersare eluted from the solid phase and detected by applying to a SELDIbiochip that binds the biomarkers and analyzing by SELDI.

The biomarkers bound to the substrates are detected in a gas phase ionspectrometer such as a time-of-flight mass spectrometer. The biomarkersare ionized by an ionization source such as a laser, the generated ionsare collected by an ion optic assembly, and then a mass analyzerdisperses and analyzes the passing ions. The detector then translatesinformation of the detected ions into mass-to-charge ratios. Detectionof a biomarker typically will involve detection of signal intensity.Thus, both the quantity and mass of the biomarker can be determined.

SEND

Another method of laser desorption mass spectrometry is calledSurface-Enhanced Neat Desorption (“SEND”). SEND involves the use ofprobes comprising energy absorbing molecules that are chemically boundto the probe surface (“SEND probe”). The phrase “energy absorbingmolecules” (EAM) denotes molecules that are capable of absorbing energyfrom a laser desorption/ionization source and, thereafter, contribute todesorption and ionization of analyte molecules in contact therewith. TheEAM category includes molecules used in MALDI, frequently referred to as“matrix,” and is exemplified by cinnamic acid derivatives, sinapinicacid (SPA), cyano-hydroxy-cinnamic acid (CHCA) and dihydroxybenzoicacid, ferulic acid, and hydroxyaceto-phenone derivatives. In certainembodiments, the energy absorbing molecule is incorporated into a linearor cross-linked polymer, e.g., a polymethacrylate. For example, thecomposition can be a co-polymer of α-cyano-4-methacryloyloxycinnamicacid and acrylate. In another embodiment, the composition is aco-polymer of α-cyano-4-methacryloyloxycinnamic acid, acrylate and3-(tri-ethoxy)silyl propyl methacrylate. In another embodiment, thecomposition is a co-polymer of α-cyano-4-methacryloyloxycinnamic acidand octadecylmethacrylate (“C18 SEND”). SEND is further described inU.S. Pat. No. 6,124,137 and PCT International Publication No. WO03/64594 (Kitagawa, “Monomers And Polymers Having Energy AbsorbingMoieties Of Use In Desorption/Ionization Of Analytes,” Aug. 7, 2003).

SEAC/SEND is a version of SELDI laser desorption mass spectrometry inwhich both a capture reagent and an energy absorbing molecule areattached to the sample presenting surface. SEAC/SEND probes thereforeallow the capture of analytes through affinity capture andionization/desorption without the need to apply external matrix. The C18SEND biochip is a version of SEAC/SEND, comprising a C18 moiety whichfunctions as a capture reagent, and a CHCA moiety which functions as anenergy absorbing moiety.

SEPAR

Another version of LDI is called Surface-Enhanced Photolabile Attachmentand Release (“SEPAR”). SEPAR involves the use of probes having moietiesattached to the surface that can covalently bind an analyte, and thenrelease the analyte through breaking a photolabile bond in the moietyafter exposure to light, e.g., to laser light (see, U.S. Pat. No.5,719,060). SEPAR and other forms of SELDI are readily adapted todetecting a biomarker or biomarker profile, pursuant to the presentinvention.

MALDI

MALDI is a traditional method of laser desorption/ionization used toanalyte biomolecules such as proteins and nucleic acids. In one MALDImethod, the sample is mixed with matrix and deposited directly on aMALDI array. However, the complexity of biological samples such as serumand urine makes this method less than optimal without priorfractionation of the sample. Accordingly, in certain embodiments withbiomarkers are preferably first captured with biospecific (e.g., anantibody) or chromatographic materials coupled to a solid support suchas a resin (e.g., in a spin column). Specific affinity materials thatbind the biomarkers of this invention are described above. Afterpurification on the affinity material, the biomarkers are eluted andthen detected by MALDI.

In another mass spectrometry method, the biomarkers can be firstcaptured on a chromatographic resin having chromatographic propertiesthat bind the biomarkers. In the present example, this could include avariety of methods. For example, one could capture the biomarkers on acation exchange resin, such as CM Ceramic HyperD F resin, wash theresin, elute the biomarkers and detect by MALDI. Alternatively, thismethod could be preceded by fractionating the sample on an anionexchange resin before application to the cation exchange resin. Inanother alternative, one could fractionate on an anion exchange resinand detect by MALDI directly. In yet another method, one could capturethe biomarkers on an immuno-chromatographic resin that comprisesantibodies that bind the biomarkers, wash the resin to remove unboundmaterial, elute the biomarkers from the resin and detect the elutedbiomarkers by MALDI or by SELDI.

Other Forms of Ionization in Mass Spectrometry

In another method, the biomarkers are detected by LC-MS or LC-LC-MS.This involves resolving the proteins in a sample by one or two passesthrough liquid chromatography, followed by mass spectrometry analysis,typically electrospray ionization.

Data Analysis

Analysis of analytes by time-of-flight mass spectrometry generates atime-of-flight spectrum. The time-of-flight spectrum ultimately analyzedtypically does not represent the signal from a single pulse of ionizingenergy against a sample, but rather the sum of signals from a number ofpulses. This reduces noise and increases dynamic range. Thistime-of-flight data is then subject to data processing. In Ciphergen'sProteinChip® software, data processing typically includes TOF-to-M/Ztransformation to generate a mass spectrum, baseline subtraction toeliminate instrument offsets and high frequency noise filtering toreduce high frequency noise.

Data generated by desorption and detection of biomarkers can be analyzedwith the use of a programmable digital computer. The computer programanalyzes the data to indicate the number of biomarkers detected, andoptionally the strength of the signal and the determined molecular massfor each biomarker detected. Data analysis can include steps ofdetermining signal strength of a biomarker and removing data deviatingfrom a predetermined statistical distribution. For example, the observedpeaks can be normalized, by calculating the height of each peak relativeto some reference. The reference can be background noise generated bythe instrument and chemicals such as the energy absorbing molecule whichis set at zero in the scale.

The computer can transform the resulting data into various formats fordisplay. The standard spectrum can be displayed, but in one usefulformat only the peak height and mass information are retained from thespectrum view, yielding a cleaner image and enabling biomarkers withnearly identical molecular weights to be more easily seen. In anotheruseful format, two or more spectra are compared, convenientlyhighlighting unique biomarkers and biomarkers that are up- ordown-regulated between samples. Using any of these formats, one canreadily determine whether a particular biomarker is present in a sample.

Analysis generally involves the identification of peaks in the spectrumthat represent signal from an analyte. Peak selection can be donevisually, but software is available, as part of Ciphergen's ProteinChip®software package, that can automate the detection of peaks. In general,this software functions by identifying signals having a signal-to-noiseratio above a selected threshold and labeling the mass of the peak atthe centroid of the peak signal. In one useful application, many spectraare compared to identify identical peaks present in some selectedpercentage of the mass spectra. One version of this software clustersall peaks appearing in the various spectra within a defined mass range,and assigns a mass (M/Z) to all the peaks that are near the mid-point ofthe mass (M/Z) cluster.

Software used to analyze the data can include code that applies analgorithm to the analysis of the signal to determine whether the signalrepresents a peak in a signal that corresponds to a biomarker accordingto the present invention. The software also can subject the dataregarding observed biomarker peaks to classification tree or ANNanalysis, to determine whether a biomarker peak or combination ofbiomarker peaks is present that indicates the status of the particularclinical parameter under examination. Analysis of the data may be“keyed” to a variety of parameters that are obtained, either directly orindirectly, from the mass spectrometric analysis of the sample. Theseparameters include, but are not limited to, the presence or absence ofone or more peaks, the shape of a peak or group of peaks, the height ofone or more peaks, the log of the height of one or more peaks, and otherarithmetic manipulations of peak height data.

General Protocol for SELDI Detection of Biomarkers for Alzheimer'sDisease

A preferred protocol for the detection of the biomarkers of thisinvention is as follows. The sample to be tested is then contacted withan affinity capture probe comprising an anion exchange adsorbent, e.g.,a Q10 ProteinChip, as indicated in Table 1. The probe is washed with abuffer that will retain the biomarker while washing away unboundmolecules. A suitable wash for the VGF peptide biomarker when binding toa Q10 ProteinChip is a 100 mM Tris buffer at pH 9. The biomarkers aredetected by laser desorption/ionization mass spectrometry.

Alternatively, if antibodies that recognize the biomarker are available,these can be attached to the surface of a probe, such as a pre-activatedPS10 or PS20 ProteinChip array (Ciphergen Biosystems, Inc.). Theseantibodies can capture the biomarkers from a sample onto the probesurface. Then the biomarkers can be detected by, e.g., laserdesorption/ionization mass spectrometry.

Detection by Immunoassay

In another embodiment of the invention, the biomarkers of the inventionare measured by a method other than mass spectrometry or other thanmethods that rely on a measurement of the mass of the biomarker. In onesuch embodiment that does not rely on mass, the biomarkers of thisinvention can be measured by immunoassay. Immunoassay requiresbiospecific capture reagents, such as antibodies, to capture thebiomarkers. Antibodies can be produced by methods well known in the art,e.g., by immunizing animals with the biomarkers. Biomarkers can beisolated from samples based on their binding characteristics.Alternatively, if the amino acid sequence of a polypeptide biomarker isknown, the polypeptide can be synthesized and used to generateantibodies by methods well known in the art.

This invention contemplates traditional immunoassays including, forexample, sandwich immunoassays including ELISA or fluorescence-basedimmunoassays, as well as other enzyme immunoassays. In the SELDI-basedimmunoassay, a biospecific capture reagent for the biomarker is attachedto the surface of an MS probe, such as a pre-activated ProteinChiparray. The biomarker is then specifically captured on the biochipthrough this reagent, and the captured biomarker is detected by massspectrometry.

V. Determination of Subject Alzheimer's Disease Status

The biomarkers of the invention can be used in diagnostic tests toassess Alzheimer's disease status in a subject, e.g., to diagnoseAlzheimer's disease. The phrase “Alzheimer's disease status” includesany distinguishable manifestation of the disease, includingnon-Alzheimer's disease, e.g., normal or non-demented. For example,disease status includes, without limitation, the presence or absence ofAlzheimer's disease (e.g., Alzheimer's disease v. non-Alzheimer'sdisease), the risk of developing disease, the stage of the disease, theprogress of disease (e.g., progress of disease or remission of diseaseover time) and the effectiveness or response to treatment of disease.Based on this status, further procedures may be indicated, includingadditional diagnostic tests or therapeutic procedures or regimens.

The power of a diagnostic test to correctly predict status is commonlymeasured as the sensitivity of the assay, the specificity of the assayor the area under a receiver operated characteristic (“ROC”) curve.Sensitivity is the percentage of true positives that are predicted by atest to be positive, while specificity is the percentage of truenegatives that are predicted by a test to be negative. An ROC curveprovides the sensitivity of a test as a function of 1-specificity. Thegreater the area under the ROC curve, the more powerful the predictivevalue of the test. Other useful measures of the utility of a test arepositive predictive value and negative predictive value. Positivepredictive value is the percentage of people who test positive that isactually positive. Negative predictive value is the percentage of peoplewho test negative that is actually negative.

The biomarkers of this invention show a statistical difference indifferent Alzheimer's disease statuses of at least p≦0.05, p≦10⁻²,p≦10⁻³, p≦10⁻⁴ or p≦10⁻⁵. Diagnostic tests that use these biomarkersalone or in combination show a sensitivity and specificity of at least75%, at least 80%, at least 85%, at least 90%, at least 95%, at least98% and about 100%.

Single Markers

VGF peptide-1 is differentially present in Alzheimer's disease, and,therefore, is individually useful in aiding in the determination ofAlzheimer's disease status. The method involves, first, measuring theVGF peptide in a subject sample using the methods described herein,e.g., capture on a SELDI biochip followed by detection by massspectrometry and, second, comparing the measurement with a diagnosticamount or cut-off that distinguishes a positive Alzheimer's diseasestatus from a negative Alzheimer's disease status. The diagnostic amountrepresents a measured amount of a biomarker above which or below which asubject is classified as having a particular Alzheimer's disease status.For example, VGF peptide is up-regulated compared to normal duringAlzheimer's disease. Therefore, a measured amount above the diagnosticcutoff provides a diagnosis of Alzheimer's disease. As is wellunderstood in the art, by adjusting the particular diagnostic cut-offused in an assay, one can increase sensitivity or specificity of thediagnostic assay depending on the preference of the diagnostician. Theparticular diagnostic cut-off can be determined, for example, bymeasuring the amount of the biomarker in a statistically significantnumber of samples from subjects with the different Alzheimer's diseasestatuses, as was done here, and drawing the cut-off to suit thediagnostician's desired levels of specificity and sensitivity.

Combinations of Markers

While individual biomarkers are useful diagnostic biomarkers, it hasbeen found that a combination of biomarkers can provide greaterpredictive value of a particular status than single biomarkers alone.Specifically, the detection of a plurality of biomarkers in a sample canincrease the sensitivity and/or specificity of the test. A combinationof at least two biomarkers is sometimes referred to as a “biomarkerprofile” or “biomarker fingerprint.”

Alzheimer's Disease Status

Determining Alzheimer's disease status typically involves classifying anindividual into one of two or more groups (statuses) based on theresults of the diagnostic test. The diagnostic tests described hereincan be used to classify between a number of different states.

Determining Presence of Disease

In one embodiment, this invention provides methods for determining thepresence or absence of Alzheimer's disease in a subject (status:Alzheimer's disease v. non-Alzheimer's disease). The presence or absenceof Alzheimer's disease is determined by measuring the relevant biomarkeror biomarkers and then either submitting them to a classificationalgorithm or comparing them with a reference amount and/or pattern ofbiomarkers that is associated with the particular risk level.

Determining Risk of Developing Disease

In one embodiment, this invention provides methods for determining therisk of developing disease in a subject. Biomarker amounts or patternsare characteristic of various risk states, e.g., high, medium or low.The risk of developing a disease is determined by measuring the relevantbiomarker or biomarkers and then either submitting them to aclassification algorithm or comparing them with a reference amountand/or pattern of biomarkers that is associated with the particular risklevel.

Determining Stage of Disease

In one embodiment, this invention provides methods for determining thestage of disease in a subject. Each stage of the disease has acharacteristic amount of a biomarker or relative amounts of a set ofbiomarkers (a pattern). The stage of a disease is determined bymeasuring the relevant biomarker or biomarkers and then eithersubmitting them to a classification algorithm or comparing them with areference amount and/or pattern of biomarkers that is associated withthe particular stage.

Determining Course (Progression/Remission) of Disease

In one embodiment, this invention provides methods for determining thecourse of disease in a subject. Disease course refers to changes indisease status over time, including disease progression (worsening) anddisease regression (improvement). Over time, the amounts or relativeamounts (e.g., the pattern) of the biomarkers changes. For example, theVGF peptide biomarker in Table 1 increases with disease. Therefore,increasing amounts of this biomarker indicates the course of thedisease. Accordingly, this method involves measuring one or morebiomarkers in a subject at two or more different time points, e.g., afirst time and a second time, and comparing the change in amounts, ifany. The course of disease is determined based on these comparisons.

Similarly, changes in the rate of disease progression (or regression)may be monitored by measuring the amount of a biomarker, e.g., the VGFpeptide biomarker of Table 1, at different times and calculating therate of change in biomarker levels. The ability to measure disease stateor velocity of disease progression can be important for drug treatmentstuides where the goal is to slow down or arrest disease progressionthrough therapy.

Reporting the Status

Similarly, changes in the rate of disease progression (or regression)may be monitored by measuring the amount of a biomarker, e.g., the VGFpeptide biomarker of Table 1, at different times and calculating therate of change in biomarker levels. The ability to measure disease stateor velocity of disease progression can be important for drug treatmentstuides where the goal is to slow down or arrest disease progressionthrough therapy.

Additional embodiments of the invention relate to the communication ofassay results or diagnoses or both to technicians, physicians orpatients, for example. In certain embodiments, computers will be used tocommunicate assay results or diagnoses or both to interested parties,e.g., physicians and their patients. In some embodiments, the assayswill be performed or the assay results analyzed in a country orjurisdiction which differs from the country or jurisdiction to which theresults or diagnoses are communicated.

In a preferred embodiment of the invention, a diagnosis based on thedifferential presence in a test subject of any the VGF peptidebiomarkers is communicated to the subject as soon as possible after thediagnosis is obtained. The diagnosis may be communicated to the subjectby the subject's treating physician. Alternatively, the diagnosis may besent to a test subject by email or communicated to the subject by phone.A computer may be used to communicate the diagnosis by email or phone.In certain embodiments, the message containing results of a diagnostictest may be generated and delivered automatically to the subject using acombination of computer hardware and software which will be familiar toartisans skilled in telecommunications. One example of ahealthcare-oriented communications system is described in U.S. Pat. No.6,283,761; however, the present invention is not limited to methodswhich utilize this particular communications system. In certainembodiments of the methods of the invention, all or some of the methodsteps, including the assaying of samples, diagnosing of diseases, andcommunicating of assay results or diagnoses, may be carried out indiverse (e.g., foreign) jurisdictions.

Subject Management

In certain embodiments of the methods of qualifying Alzheimer's diseasestatus, the methods further comprise managing subject treatment based onthe status. Such management includes the actions of the physician orclinician subsequent to determining Alzheimer's disease status. Forexample, if a physician makes a diagnosis of Alzheimer's disease, then acertain regime of treatment, such as prescription or administration of acholinesterase inhibitor might follow. Alternatively, a diagnosis ofnon-Alzheimer's disease or non-Alzheimer's disease might be followedwith further testing to determine a specific disease that might thepatient might be suffering from. Also, if the diagnostic test gives aninconclusive result on Alzheimer's disease status, further tests may becalled for.

Additional embodiments of the invention relate to the communication ofassay results or diagnoses or both to technicians, physicians orpatients, for example. In certain embodiments, computers will be used tocommunicate assay results or diagnoses or both to interested parties,e.g., physicians and their patients. In some embodiments, the assayswill be performed or the assay results analyzed in a country orjurisdiction which differs from the country or jurisdiction to which theresults or diagnoses are communicated.

In a preferred embodiment of the invention, a diagnosis based on thepresence or absence in a test subject of the VGF peptide of Table 1 iscommunicated to the subject as soon as possible after the diagnosis isobtained. The diagnosis may be communicated to the subject by thesubject's treating physician. Alternatively, the diagnosis may be sentto a test subject by email or communicated to the subject by phone. Acomputer may be used to communicate the diagnosis by email or phone. Incertain embodiments, the message containing results of a diagnostic testmay be generated and delivered automatically to the subject using acombination of computer hardware and software which will be familiar toartisans skilled in telecommunications. One example of ahealthcare-oriented communications system is described in U.S. Pat. No.6,283,761; however, the present invention is not limited to methodswhich utilize this particular communications system. In certainembodiments of the methods of the invention, all or some of the methodsteps, including the assaying of samples, diagnosing of diseases, andcommunicating of assay results or diagnoses, may be carried out indiverse (e.g., foreign) jurisdictions.

VI. Determining Therapeutic Efficacy of Pharmaceutical Drug

In another embodiment, this invention provides methods for determiningthe therapeutic efficacy of a pharmaceutical drug. These methods areuseful in performing clinical trials of the drug, as well as monitoringthe progress of a patient on the drug. Therapy or clinical trialsinvolve administering the drug in a particular regimen. The regimen mayinvolve a single dose of the drug or multiple doses of the drug overtime. The doctor or clinical researcher monitors the effect of the drugon the patient or subject over the course of administration. If the drughas a pharmacological impact on the condition, the amounts or relativeamounts (e.g., the pattern or profile) of the biomarkers of thisinvention changes toward a non-disease profile. For example, VGF peptidebiomarker is increased in disease. Therefore, one can follow the courseof the amounts of these biomarkers in the subject during the course oftreatment. Accordingly, this method involves measuring one or morebiomarkers in a subject receiving drug therapy, and correlating theamounts of the biomarkers with the disease status of the subject. Oneembodiment of this method involves determining the levels of thebiomarkers at at least two different time points during a course of drugtherapy, e.g., a first time and a second time, and comparing the changein amounts of the biomarkers, if any. For example, the biomarkers can bemeasured before and after drug administration or at two different timepoints during drug administration. The effect of therapy is determinedbased on these comparisons. If a treatment is effective, then thebiomarkers will trend toward normal, while if treatment is ineffective,the biomarkers will trend toward disease indications. If a treatment iseffective, then the biomarkers will trend toward normal, while iftreatment is ineffective, the biomarkers will trend toward diseaseindications.

VII. Generation of Classification Algorithms for Qualifying Alzheimer'SDisease Status

In some embodiments, data derived from the spectra (e.g., mass spectraor time-of-flight spectra) that are generated using samples such as“known samples” can then be used to “train” a classification model. A“known sample” is a sample that has been pre-classified. The data thatare derived from the spectra and are used to form the classificationmodel can be referred to as a “training data set.” Once trained, theclassification model can recognize patterns in data derived from spectragenerated using unknown samples. The classification model can then beused to classify the unknown samples into classes. This can be useful,for example, in predicting whether or not a particular biological sampleis associated with a certain biological condition (e.g., diseased versusnon-diseased).

The training data set that is used to form the classification model maycomprise raw data or pre-processed data. In some embodiments, raw datacan be obtained directly from time-of-flight spectra or mass spectra,and then may be optionally “pre-processed” as described above.

Classification models can be formed using any suitable statisticalclassification (or “learning”) method that attempts to segregate bodiesof data into classes based on objective parameters present in the data.Classification methods may be either supervised or unsupervised.Examples of supervised and unsupervised classification processes aredescribed in Jain, “Statistical Pattern Recognition: A Review”, IEEETransactions on Pattern Analysis and Machine Intelligence, Vol. 22, No.1, January 2000, the teachings of which are incorporated by reference.

In supervised classification, training data containing examples of knowncategories are presented to a learning mechanism, which learns one ormore sets of relationships that define each of the known classes. Newdata may then be applied to the learning mechanism, which thenclassifies the new data using the learned relationships. Examples ofsupervised classification processes include linear regression processes(e.g., multiple linear regression (MLR), partial least squares (PLS)regression and principal components regression (PCR)), binary decisiontrees (e.g., recursive partitioning processes such asCART—classification and regression trees), artificial neural networkssuch as back propagation networks, discriminant analyses (e.g., Bayesianclassifier or Fischer analysis), logistic classifiers, and supportvector classifiers (support vector machines).

A preferred supervised classification method is a recursive partitioningprocess. Recursive partitioning processes use recursive partitioningtrees to classify spectra derived from unknown samples. Further detailsabout recursive partitioning processes are provided in U.S. PatentApplication No. 2002 0138208 A1 to Paulse et al., “Method for analyzingmass spectra.”

In other embodiments, the classification models that are created can beformed using unsupervised learning methods. Unsupervised classificationattempts to learn classifications based on similarities in the trainingdata set, without pre-classifying the spectra from which the trainingdata set was derived. Unsupervised learning methods include clusteranalyses. A cluster analysis attempts to divide the data into “clusters”or groups that ideally should have members that are very similar to eachother, and very dissimilar to members of other clusters. Similarity isthen measured using some distance metric, which measures the distancebetween data items, and clusters together data items that are closer toeach other. Clustering techniques include the MacQueen's K-meansalgorithm and the Kohonen's Self-Organizing Map algorithm.

Learning algorithms asserted for use in classifying biologicalinformation are described, for example, in PCT International PublicationNo. WO 01/31580 (Barnhill et al., “Methods and devices for identifyingpatterns in biological systems and methods of use thereof”), U.S. PatentApplication No. 2002 0193950 A1 (Gavin et al., “Method or analyzing massspectra”), U.S. Patent Application No. 2003 0004402 A1 (Hitt et al.,“Process for discriminating between biological states based on hiddenpatterns from biological data”), and U.S. Patent Application No. 20030055615 A1 (Zhang and Zhang, “Systems and methods for processingbiological expression data”).

The classification models can be formed on and used on any suitabledigital computer. Suitable digital computers include micro, mini, orlarge computers using any standard or specialized operating system, suchas a Unix, Windows™ or Linux™ based operating system. The digitalcomputer that is used may be physically separate from the massspectrometer that is used to create the spectra of interest, or it maybe coupled to the mass spectrometer.

The training data set and the classification models according toembodiments of the invention can be embodied by computer code that isexecuted or used by a digital computer. The computer code can be storedon any suitable computer readable media including optical or magneticdisks, sticks, tapes, etc., and can be written in any suitable computerprogramming language including C, C++, visual basic, etc.

The learning algorithms described above are useful both for developingclassification algorithms for the biomarkers already discovered, or forfinding new biomarkers for Alzheimer's disease. The classificationalgorithms, in turn, form the base for diagnostic tests by providingdiagnostic values (e.g., cut-off points) for biomarkers used singly orin combination.

VIII. Use of Biomarkers for Imaging

Non-invasive medical imaging techniques such as Positron EmissonTomography (PET) or single photon emission computerized tomography(SPECT) imaging are particularly useful for the detection of cancer,coronary artery disease and brain disease. PET and SPECT imaging showsthe chemical functioning of organs and tissues, while other imagingtechniques—such as X-ray, CT and MRI—show structure. The use of PET andSPECT imaging has become increasingly useful for qualifying andmonitoring the development of brain diseases such as Alzheimer'sdisease. In some instances, the use of PET or SPECT imaging allowsAlzheimer's disease to be detected several years earlier than the onsetof symptoms. See, e.g., Vassaux and Groot-wassink, “In Vivo NoninvasiveImaging for Gene Therapy,” J. Biomedicine and Biotechnology, 2: 92-101(2003).

Different strategies are being used to develop compounds suitable for invivo imaging of amyloid deposits in human brains. Monoclonal antibodiesagainst A-beta and peptide fragments have had limited uptake by thebrain when tested in patients with AD. The small molecular approach foramyloid imaging has so far been most successful, as described by, e.g.,Nordberg A, Lancet Neurol., 3(9):519-27 (2004); Kung M P et al, BrainRes., 1025(1-2):98-105 (2004); Herholz K et al., Mol Imaging Biol.,6(4):239-69 (2004); Neuropsychol Rev., Zakzanis K K et al., 13(1):1-18(2003); Herholz K, Ann Nucl Med., 17(2):79-89 (2003).

The peptide biomarkers disclosed herein, or fragments thereof, can beused in the context of PET and SPECT imaging applications. Aftermodification with appropriate tracer residues for PET or SPECTapplications, peptide biomarkers which interact with amyloid plaqueproteins can be used to image the deposition of amyloid plaques inAlzheimer's patients.

Antisense technology may be used to detect expression of transcriptswhose translation is correlated with the biomarkers identified herein.For example, the use of antisense peptide nucleic acid (PNA) labeledwith an appropriate radionuclide, such as ¹¹¹In, and conjugated to abrain drug-targeting system to enable transport across biologic membranebarriers, has been demonstrated to allow imaging of endogenous geneexpression in brain cancer. See Suzuki et al., Journal of NuclearMedicine, 10: 1766-1775 (2004). Suzuki et al. utilize a delivery systemcomprising monoclonal antibodies that target transferring receptors atthe blood-brain barrier and facilitate transport of the PNA across thatbarrier.

IX. Compositions of Matter

In another aspect, this invention provides compositions of matter basedon the biomarkers of this invention.

In one embodiment, this invention provides biomarkers of this inventionin purified form. Purified biomarkers have utility as antigens to raiseantibodies. Purified biomarkers also have utility as standards in assayprocedures. As used herein, a “purified biomarker” is a biomarker thathas been isolated from other proteins and peptdies, and/or othermaterial from the biological sample in which the biomarker is found.Biomarkers may be purified using any method known in the art, including,but not limited to, mechanical separation (e.g., centrifugation),ammonium sulphate precipitation, dialysis (including size-exclusiondialysis), size-exclusion chromatography, affinity chromatography,anion-exchange chromatography, cation-exchange chromatography, andmetal-chelate chrmatography. Such methods may be performed at anyappropriate scale, for example, in a chromatography column, or on abiochip.

In another embodiment, this invention provides biospecific capturereagents that specifically bind a biomarker of this invention,optionally in purified form. Preferably, a biospecific capture reagentis an antibody. In one embodiment, a biospecific capture reagent is anantibody that binds a biomarker of this invention.

In another embodiment, this invention provides a complex between abiomarker of this invention and biospecific capture reagent thatspecifically binds the biomarker. In other embodiments, the biospecificcapture reagent is bound to a solid phase. For example, this inventioncontemplates a device comprising bead or chip derivatized with abiospecific capture reagent that binds to a biomarker of this inventionand, also, the device in which a biomarker of this invention is bound tothe biospecific capture reagent.

In another embodiment, this invention provides a device comprising asolid substrate to which is attached an adsorbent, e.g., achromatographic adsorbent, to which is further bound a biomarker of thisinvention.

X. Kits for Detection of Biomarkers for Alzheimer's Disease

In another aspect, the present invention provides kits for qualifyingAlzheimer's disease status, which kits are used to detect biomarkersaccording to the invention. In one embodiment, the kit comprises a solidsupport, such as a chip, a microtiter plate or a bead or resin having acapture reagent attached thereon, wherein the capture reagent binds abiomarker of the invention. Thus, for example, the kits of the presentinvention can comprise mass spectrometry probes for SELDI, such asProteinChip® arrays. In the case of biospecfic capture reagents, the kitcan comprise a solid support with a reactive surface, and a containercomprising the biospecific capture reagent.

The kit can also comprise a washing solution or instructions for makinga washing solution, in which the combination of the capture reagent andthe washing solution allows capture of the biomarker or biomarkers onthe solid support for subsequent detection by, e.g., mass spectrometry.The kit may include more than type of adsorbent, each present on adifferent solid support.

In a further embodiment, such a kit can comprise instructions forsuitable operational parameters in the form of a label or separateinsert. For example, the instructions may inform a consumer about how tocollect the sample, how to wash the probe or the particular biomarkersto be detected.

In yet another embodiment, the kit can comprise one or more containerswith biomarker samples, to be used as standard(s) for calibration.

XI. Use of Biomarkers for Alzheimer's Disease in Screening Assays andMethods of Treating Alzheimer's Disease

The methods of the present invention have other applications as well.For example, the biomarkers can be used to screen for compounds thatmodulate the expression of the biomarkers in vitro or in vivo, whichcompounds in turn may be useful in treating or preventing Alzheimer'sdisease in patients. In another example, the biomarkers can be used tomonitor the response to treatments for Alzheimer's disease. In yetanother example, the biomarkers can be used in heredity studies todetermine if the subject is at risk for developing Alzheimer's disease.

Thus, for example, the kits of this invention could include a solidsubstrate having a hydrophobic function, such as a protein biochip(e.g., a Ciphergen Q10 ProteinChip array, e.g., ProteinChip array) and asodium acetate buffer for washing the substrate, as well as instructionsproviding a protocol to measure the biomarkers of this invention on thechip and to use these measurements to diagnose Alzheimer's disease.

Compounds suitable for therapeutic testing may be screened initially byidentifying compounds which interact with one or more biomarkers listedin Table I. By way of example, screening might include recombinantlyexpressing a biomarker listed in Table I, purifying the biomarker, andaffixing the biomarker to a substrate. Test compounds would then becontacted with the substrate, typically in aqueous conditions, andinteractions between the test compound and the biomarker are measured,for example, by measuring elution rates as a function of saltconcentration. Certain proteins may recognize and cleave one or morebiomarkers of Table I, in which case the proteins may be detected bymonitoring the digestion of one or more biomarkers in a standard assay,e.g., by gel electrophoresis of the proteins.

In a related embodiment, the ability of a test compound to inhibit theactivity of VGF peptide may be measured. One skilled in the art willrecognize that the techniques used to measure the activity of aparticular biomarker will vary depending on the function and propertiesof the biomarker. For example, an enzymatic activity of a biomarker maybe assayed provided that an appropriate substrate is available andprovided that the concentration of the substrate or the appearance ofthe reaction product is readily measurable. The ability of potentiallytherapeutic test compounds to inhibit or enhance the activity of a givenbiomarker may be determined by measuring the rates of catalysis in thepresence or absence of the test compounds. The ability of a testcompound to interfere with a non-enzymatic (e.g., structural) functionor activity of one of the biomarkers of Table I may also be measured.For example, the self-assembly of a multi-protein complex which includesthe VGF peptide may be monitored by spectroscopy in the presence orabsence of a test compound. Alternatively, if the biomarker is anon-enzymatic enhancer of transcription, test compounds which interferewith the ability of the biomarker to enhance transcription may beidentified by measuring the levels of biomarker-dependent transcriptionin vivo or in vitro in the presence and absence of the test compound.

Test compounds capable of modulating the activity of the VGF peptide maybe administered to patients who are suffering from or are at risk ofdeveloping Alzheimer's disease or other cancer. For example, theadministration of a test compound which increases the activity of aparticular biomarker may decrease the risk of Alzheimer's disease in apatient if the activity of the particular biomarker in vivo prevents theaccumulation of proteins for Alzheimer's disease. Conversely, theadministration of a test compound which decreases the activity of aparticular biomarker may decrease the risk of Alzheimer's disease in apatient if the increased activity of the biomarker is responsible, atleast in part, for the onset of Alzheimer's disease.

In an additional aspect, the invention provides a method for identifyingcompounds useful for the treatment of disorders such as Alzheimer'sdisease which are associated with increased levels of modified forms ofa native protein. For example, in one embodiment, cell extracts orexpression libraries may be screened for compounds which catalyze thecleavage of full-length VGF protein to form the VGF peptide of Table 1.In one embodiment of such a screening assay, cleavage of native VGFprotein or the VGF peptide may be detected by attaching a fluorophore tothe protein which remains quenched when protein is uncleaved but whichfluoresces when the protein is cleaved. Alternatively, a modifiedversion of VGF where the amide bond between the amino acids at the N-and C-terminus of the VGF peptide uncleavable may be used to selectivelybind or “trap” the cellular protesase which cleaves full-length VGFprotein at that site in vivo. Methods for screening and identifyingproteases and their targets are well-documented in the scientificliterature, e.g., in Lopez-Ottin et al. (Nature Reviews, 3:509-519(2002)).

At the clinical level, screening a test compound for use in treatingAlzheimer's disease includes obtaining samples from test subjects beforeand after the subjects have been exposed to a test compound. The levelsin the samples of the VGF peptide of Table 1 may be measured andanalyzed to determine whether the levels of the biomarkers change afterexposure to a test compound. The samples may be analyzed by massspectrometry, as described herein, or the samples may be analyzed by anyappropriate means known to one of skill in the art. For example, thelevels of one or more of the biomarkers listed in Table I may bemeasured directly by Western blot using radio- or fluorescently-labeledantibodies which specifically bind to the biomarkers. Alternatively,changes in the levels of mRNA encoding the one or more biomarkers may bemeasured and correlated with the administration of a given test compoundto a subject. In a further embodiment, the changes in the level ofexpression of one or more of the biomarkers may be measured using invitro methods and materials. For example, human tissue cultured cellswhich express, or are capable of expressing, one or more of thebiomarkers of Table I may be contacted with test compounds. Subjects whohave been treated with test compounds will be routinely examined for anyphysiological effects which may result from the treatment. Inparticular, the test compounds will be evaluated for their ability todecrease disease likelihood in a subject. Alternatively, if the testcompounds are administered to subjects who have previously beendiagnosed with Alzheimer's disease, test compounds will be screened fortheir ability to slow or stop the progression of the disease.

XII. Examples Example 1 Discovery of Biomarkers for Alzheimer's Disease

Materials and Methods

Study design and clinical samples: CSF samples (150 μl) from 97Alzheimer's disease patients (age: Mean 74.11, Range 50-89) including 83very mild cases with a Mini-Mental State Examination (MMSE) of >24 and49 Normal individuals (age: Mean 62.94, Range 39-92) were used in thisstudy (see Table 3). TABLE 3 Clinical Characteristics Diagnosis NoGender (M:F) Age (y) MMSE score Probable AD 97 27:70 74.1 (7.4)  24.9(3.8) Normal 49 22:27 62.9 (12.8) 28.3 (2.4)Values are means (SD).

All patients underwent a thorough clinical investigation that includedthe following: medical (including history); physical, neurological, andpsychiatric examinations; screening laboratory tests; anelectroencephalogram; and a computerized tomography scan of the brain.The presence or absence of dementia was diagnosed according to DSM-IVcriteria. Probable AD was diagnosed according to NINCDS-ADRDA criteria(McKhann G. et al. (1984) Neurology 34:939-944) and disease severity wasassessed using MMSE scores (Folstein M F et al., (1975) J Psychiatr Res12:189-198).

CSF samples were obtained by lumbar puncture in the L3/L4 or L4/L5interspace, collected in polypropylene tubes and stored at −80° C. Allpatients (or their nearest relatives) and normal individuals gaveinformed consent to participate in the study, which was conductedaccording to the Helsinki Declaration. The CSF samples were sourcedthrough three specialized centers at Piteä River Valley Hospital inSweden (AD site 1, N=64), University of Kuopio in Finland (AD site 2,N=33) and University of Gottenburg in Sweden (Normal, N=49). The samplesalong with pooled reference CSF were aliquoted into 96-well microtiterplates with randomized placement to help eliminate systematic bias.

SELDI analysis: Clinical CSF samples were thawed, and 5 μl of eachsample was diluted into 50 μl of the appropriate binding buffer andprofiled on a range of ProteinChip® Array types (Ciphergen Biosystems,Fremont, Calif.). All array preparation was performed using a Biomek®2000 robot (Beckman Coulter) with an integrated shaker and randomizedsample placement. The following binding buffers were used for eachProteinChip Array type: 10% acetonitrile with 0.1% trifluoroacetic acidfor H50 arrays, 100 mM Sodium Phosphate (pH 7.0, 0.5 M NaCl) forIMAC30-Cu arrays, 100 mM Sodium Acetate (pH 4.0) for CM10 arrays, and100 mM Tris (pH 9.0) for Q10 arrays. The samples were allowed to bindfor 30 minutes at room temperature. Each array was washed three timeswith the appropriate binding buffer and rinsed twice with water beforethe addition of Energy Absorbing Molecules (EAM) used for facilitatingdesorption and ionization of proteins in the mass spectrometer reader.Sinapinic Acid (SPA) and 4-hydroxy-alpha-cyanocinnamic acid (CHCA) wereused as EAMs (Ciphergen Biosystems, Fremont, Calif.). The arrays withSPA were read at two different instrument settings to focus on lower andhigher masses while CHCA readings focused on the lower mass region (theVGF peptide in Table 1 was identified using a high energy instrumentsetting). Each sample was run in triplicate on separate arrays onsuccessive days. Analysis of the arrays was performed in a ProteinChipReader, series PBS (IIc) (Ciphergen Biosystems, Fremont, Calif.). Aprotein retentate map was generated in which the individual proteinswere displayed as unique peaks based on their mass and charge (m/z).

To ensure reproducibility of sample preparation and array analysis, areference CSF standard was randomly distributed in several separatealiquots among the clinical samples and analyzed under exactly the sameconditions. Reproducibility was measured as pooled coefficients ofvariation (CV) for each set of acquisition parameters. The CV valueswere determined to be 20-25% (N=28) and were independent of array lot.

Data Analysis: ProteinChip profiling spectral data were collected usingProteinChip Software version 3.1 and directly exported toCiphergenExpress™ Software version 3.0, where data handling andunivariate analysis were performed. All spectra were mass calibratedinternally and peak intensities were normalized. Peak clustering wasperformed in a range that excluded the very low mass region, which isdominated by EAM peaks. P values for individual peaks across each groupwere calculated using a Mann-Whitney test. The AUC of the receiveroperator characteristic curve (ROC AUC) was calculated for each peak andthe number of features reduced by keeping only peaks with values above0.65. All peaks showing a significant difference in the initialunivariate analysis were checked manually to exclude any spurious peaks.For further data reduction, the AD samples were compared separately bysite, i.e., Swedish (AD site 1) vs. healthy controls and Finnish (ADsite 2) vs. healthy controls, to select candidate biomarkers with ROCAUC values above 0.65 in both comparisons and changed in the samedirection.

Marker purification and ID: Biomarkers were purified using combinationsof chromatographic techniques employing a range of Biosepra sorbentstypically followed by SDS-PAGE. The purification schemes were monitoredusing a ProteinChip Reader to track biomarkers of interest. For proteinssmaller than 30 kDa, intact bands of interest were extracted from gelsand reanalyzed using the ProteinChip Reader to confirm their exactmasses matched with the original biomarker. The gel-extracted proteinswere in-solution digested with trypsin and proteins larger than 30 kDawere in-gel digested. Tryptic digests were analyzed by peptide mappingusing the ProteinChip Reader and by tandem MS using a Q-STAR (AppliedBiosystems) instrument fitted with a PCI-1000 ProteinChip Interface.Biomarkers smaller than 4 kDa were enriched by combinations ofchromatographic techniques and identified directly by tandem MS withoutSDS-PAGE purification and/or trypsin digestion.

The techniques described in the preceding paragraph allowed theidentification of the VGF peptide biomarker of Table 1.

The VGF peptide of Table 1 is derived from the neurosecretory proteinVFG described in the Swiss Protein Database as VGF_HUMAN (015240) (aminoacids 23 to 616). The deposited sequence appears below: 1 MKALRLSASALFCLLLINGL GAAPPGRPEA QPPPLSSEHK EPVAGDAVPG PKDGSAPEVR 60 61 GARNSEPQDEGELFQGVDPR ALAAVLLQAL DRPASPPAPS GSQQGPEEEA AEALLTETVR 120 121SQTHSLPAAG EPEPAAPPRP QTPENGPEAS DPSEELEALA SLLQELRDFS PSSAKRQQET 180181 AAAETETRTH TLTRVNLESP GPERVWRASW GEFQARVPER APLPPPAPSQ FQARMPDSGP240 241 LPETHKFGEG VSSPKTHLGE ALAPLSKAYQ GVAAPFPKAR RAESALLGGSEAGERLLQQG 300 301 LAQVEAGRRQ AEATRQAAAQ EERLADLASD LLLQYLLQGGARQRGLGGRG LQEAAEERES 360 361 AREEEEAEQE RRGGEERVGE EDEEAAEAAEAEADEAERAR QNALLFAEEE DGEAGAEDKR 420 421SQEETPGHRR KEAEGTEEGG EEEDDEEMDP QTIDSLIELS TKLHLPADDV VSIIEEVEEK 480481 RNRKKKAPPE PVPPPRAAPA PTHVRSPQPP PPPPSARDEL PDWNEVLPPW DREEDEVYPP540 541 GPYHPFPNYI RPRTLQPPSA LRRRHYHHAL PPSRHYPGRE AQARHAQQEEAEAEERRLQE 600 601 QEELENYIEH VLLRRP

The peptide corresponding to the 6620 Da biomarker is underlined (aminoacids 421-479; theoretical MW 6621.98, pI 3.98) (SEQ ID NO. 1). Thesequenced tryptic peptides are highlighted in bold. This peptide islikely excised from the precursor by prohormone convertases at -KR-cleavage sites, as observed for other peptides derived fromsecretogranins and chromogranins. Neurosecretory protein VGF istranscribed solely in subpopulations of neuroendocrine cells in vivo andit is induced by neurotrophins in target cells in vitro (Canu N et al.,Genomics. 1997 Oct. 15; 45(2):443-6); Levi A et al., Cell Mol Neurobiol.2004 August; 24(4):517-33)).

It is understood that the examples and embodiments described herein arefor illustrative purposes only and that various modifications or changesin light thereof will be suggested to persons skilled in the art and areto be included within the spirit and purview of this application andscope of the appended claims. All publications, patents, and patentapplications cited herein are hereby incorporated by reference in theirentirety for all purposes.

1. A method for qualifying Alzheimer's disease status in a subjectcomprising: (a) measuring at least VGF peptide-1 in a biological samplefrom the subject; and (b) correlating the measurement with Alzheimer'sdisease status.
 2. The method of claim 1, wherein the biomarker ismeasured by capturing the biomarker on an adsorbent surface of a SELDIprobe and detecting the captured biomarkers by laserdesorption-ionization mass spectrometry.
 3. The method of claim 2,wherein the adsorbent is an anion-exchange adsorbent.
 4. The method ofclaim 2, wherein the adsorbent is a biospecific adsorbent.
 5. The methodof claim 1, wherein VGF peptide-1 is M6608.
 6. The method of claim 1,wherein VGF peptide-1 is measured by a method that does not involvemeasuring the mass of VGF peptide-1.
 7. The method of claim 6, whereinthe method involves an immunoassay.
 8. The method of claim 1, whereinthe sample is cerebrospinal fluid.
 9. The method of claim 1, wherein thecorrelating is performed by a software classification algorithm.
 10. Themethod of claim 1, wherein Alzheimer's disease status is selected fromAlzheimer's disease and non-Alzheimer's disease.
 11. The method of claim1, further comprising: (c) reporting the status to the subject.
 12. Themethod of claim 1, further comprising: (c) recording the status on atangible medium.
 13. The method of claim 1, further comprising: (c)managing subject treatment based on the status.
 14. The method of claim13, further comprising: (d) measuring VGF peptide-1 after subjectmanagement and correlating the measurement with disease progression. 15.The method of claim 13, wherein, if the measurement correlates withAlzheimer's disease, then managing subject treatment comprisesadministering a cholinesterase inhibitor to the subject.
 16. The methodof claim 7, further comprising: (d) measuring the at least one biomarkerafter subject management and correlating the measurement with diseaseprogression.
 17. A method for determining the course of Alzheimer'sdisease comprising: (a) measuring VGF peptide-1 in a subject sample at afirst time; (b) measuring VGF peptide-1 in a subject sample at a secondtime; and (c) comparing the first measurement and the secondmeasurement; wherein the comparative measurements determine the courseof the Alzheimer's disease in the subject.
 18. A method comprisingmeasuring VGF peptide-1 in a sample from a subject.
 19. A compositioncomprising a purified VGF peptide-1.
 20. A composition comprising abiospecific capture reagent that specifically binds VGF peptide-1. 21.The composition of claim 20, wherein the biospecific capture reagent isan antibody.
 22. The composition of claim 20, wherein the biospecificcapture reagent is bound to a solid support.
 23. A compositioncomprising a biospecific capture reagent bound to VGF peptide-1.
 24. Akit comprising: (a) a solid support comprising at least one capturereagent attached thereto, wherein the capture reagent binds VGFpeptide-1; and (b) instructions for using the solid support to detectsaid VGF peptide-1.
 25. The kit of claim 24 comprising instructions forusing the solid support to detect said VGF peptide-1.
 26. The kit ofclaim 24 wherein the solid support comprising a capture reagent is aSELDI probe.
 27. The kit of claim 24 wherein the capture reagent is ananion-exchange adsorbent.
 28. The kit of claim 24, additionallycomprising: (c) a container containing VGF peptide-1.
 29. The kit ofclaim 24, additionally comprising: (c) an anion-exchange chromatographysorbent.
 30. A kit comprising: (a) a solid support comprising at leastone capture reagent attached thereto, wherein the capture reagents bindsVGF peptide-1; and (b) a container containing VGF peptide-1.
 31. The kitof claim 30, wherein the solid support comprising a capture reagent is aSELDI probe.
 32. The kit of claim 30, additionally comprising: (c) ananion-exchange chromatography sorbent.
 33. A software productcomprising: a. code that accesses data attributed to a sample, the datacomprising measurement of VGF peptide-1; and b. code that executes aclassification algorithm that classifies the Alzheimer's disease statusof the sample as a function of the measurement.
 34. A method comprisingdetecting VGF peptide-1 in a sample.
 35. A method comprisingcommunicating to a subject a diagnosis relating to Alzheimer's diseasestatus determined from the correlation of at least VGF peptide-1 in asample from the subject.
 36. The method of claim 35, wherein thediagnosis is communicated to the subject via a computer-generatedmedium.
 37. A method for identifying a compound that interacts with VGFpeptide-1, wherein said method comprises: a) contacting said biomarkerwith a test compound; and b) determining whether the test compoundinteracts with said biomarker.
 38. A method for modulating theconcentration of the VGF peptide-1 in a cell, wherein said methodcomprises: a) contacting said cell with a protease inhibitor, whereinsaid protease inhibitor prevents cleavage of native VGF protein.
 39. Amethod of treating a condition in a subject, wherein said methodcomprises: administering to a subject a therapeutically effective amountof a protease inhibitor, wherein said protease inhibitor preventscleavage of native VGF protein.
 40. The method of claim 39 wherein saidcondition is Alzheimer's disease.